A Bayesian Adjustment for Covariate Misclassification with Correlated Binary Outcome Data

Estimated associations between an outcome variable and misclassified covariates tend to be biased when the methods of estimation that ignore the classification error are applied. Available methods to account for misclassification often require the use of a validation sample (i.e. a gold standard). In practice, however, such a gold standard may be unavailable or impractical. We propose a Bayesian approach to adjust for misclassification in a binary covariate in the random effect logistic model when a gold standard is not available. This Markov Chain Monte Carlo (MCMC) approach uses two imperfect measures of a dichotomous exposure under the assumptions of conditional independence and non-differential misclassification. A simulated numerical example and a real clinical example are given to illustrate the proposed approach. Our results suggest that the estimated log odds of inpatient care and the corresponding standard deviation are much larger in our proposed method compared with the models ignoring misclassification. Ignoring misclassification produces downwardly biased estimates and underestimate uncertainty.     

Non-ignorable missing covariate data in survival analysis: a case-study of an International Breast Cancer Study Group trial

Summary.  Non-ignorable missing data, a serious problem in both clinical trials and observational studies, can lead to biased inferences. Quality-of-life measures have become increasingly popular in clinical trials. However, these measures are often incompletely observed, and investigators may suspect that missing quality-of-life data are likely to be non-ignorable. Although several recent references have addressed missing covariates in survival analysis, they all required the assumption that missingness is at random or that all covariates are discrete. We present a method for estimating the parameters in the Cox proportional hazards model when missing covariates may be non-ignorable and continuous or discrete. Our method is useful in reducing the bias and improving efficiency in the presence of missing data. The methodology clearly specifies assumptions about the missing data mechanism and, through sensitivity analysis, helps investigators to understand the potential effect of missing data on study results.     

汉武封禅:儒学正统化大典

汉武时代,形势需要有一种主导性的价值观念来强化皇权、开拓大一统帝国和维护社会秩序,儒学思想应运登上政治舞台。在儒学思想诠释与演绎下,封禅仪式程序不仅成为改德改制、大一统宗教礼仪和皇权至上与“奉天承运”的标志,而且也是宣告儒学正统化、制度化的典礼。     

Choice of the primary analysis in longitudinal clinical trials

Missing data, and the bias they can cause, are an almost ever‐present concern in clinical trials. The last observation carried forward (LOCF) approach has been frequently utilized to handle missing data in clinical trials, and is often specified in conjunction with analysis of variance (LOCF ANOVA) for the primary analysis. Considerable advances in statistical methodology, and in our ability to implement these methods, have been made in recent years. Likelihood‐based, mixed‐effects model approaches implemented under the missing at random (MAR) framework are now easy to implement, and are commonly used to analyse clinical trial data. Furthermore, such approaches are more robust to the biases from missing data, and provide better control of Type I and Type II errors than LOCF ANOVA. Empirical research and analytic proof have demonstrated that the behaviour of LOCF is uncertain, and in many situations it has not been conservative. Using LOCF as a composite measure of safety, tolerability and efficacy can lead to erroneous conclusions regarding the effectiveness of a drug. This approach also violates the fundamental basis of statistics as it involves testing an outcome that is not a physical parameter of the population, but rather a quantity that can be influenced by investigator behaviour, trial design, etc. Practice should shift away from using LOCF ANOVA as the primary analysis and focus on likelihood‐based, mixed‐effects model approaches developed under the MAR framework, with missing not at random methods used to assess robustness of the primary analysis. Copyright © 2004 John Wiley & Sons, Ltd.     

数控机床功能的扩展

本文主要分析了HEIDENHAIN TNC 310数控铣床系统中圆弧铣削指令及螺纹铣削指令,对螺纹铣削功能进行延伸,扩展到圆弧三轴联动,并对螺纹铣削指令格式进行了修改,从而具有圆弧三轴联动铣削功能。     

A note on interval‐censored lifetime data and the constant‐sum condition of oiler,gómez & calle (2004)

Oiler, Gomez & Calle (2004) give a constant sum condition for processes that generate interval‐censored lifetime data. They show that in models satisfying this condition, it is possible to estimate non‐parametrically the lifetime distribution based on a well‐known simplified likelihood. The author shows that this constant‐sum condition is equivalent to the existence of an observation process that is independent of lifetimes and which gives the same probability distribution for the observed data as the underlying true process.     

虢国车马坑葬初探

三门峡上村岭虢国墓地车马坑是迄今为止发现的西周春秋时期规模较大、等级齐全、排列有序的贵族墓祔葬车马坑。虢国车马坑葬继承和沿用商周车马殉葬制，又适应和迎合社会进步及变革需要，对车马坑的殉葬内容和形式进行变通与革新，摒弃车葬坑和同穴葬，整车葬成为主流形式，并盛行车马葬和异穴葬，车马排列有序，殉葬性质更加明确，是象征性、明器化殉葬的滥觞，殉人制消失，显示出传统车马坑葬制开始出现瓦解的苗头。大量车马坑葬在虢国墓地出现，反映了虢国生产力发展水平和崇勇尚武世风，更反映了车马坑主人的身份等级，它与列鼎制紧密配合，形成了一个不可分割的整体。     

关于我国经济特区发展的几点思考

特区的“特”与“不特”，是个关系到经济特区发展的大问题。本文从世界、全国和特区３个视野探讨了这个问题，认为特区要进一步发展，必须顺应世界经济特区发展的趋势，从全国改革开放和现代化建设的大局出发，充分发挥各自的特色，再创特区发展的新优势。     

论高师思想政治教育专业的创新教育

高师思想政治教育专业要面对21世纪的机遇与挑战,就必须转变教育思想和观念,从社会主义市场经济、知识经济需要出发建构创新的课程体系,确立多元化的培养目标、培养模式,实现课程综合化,树立全面发展的、开放的、职业化的人才创新理念.     

刑法溯及力原则立法上的缺失——兼论中间时法的生存之理

<中华人民共和国刑法>对溯及力问题作了从旧兼从轻的原则性规定,这是我国刑法向科学化、民主化方向发展的重要表现,然而刑法在其动态运行中又产生了中间时法的问题.本文通过对中间时法的产生及其机理的分析,并结合中间时法在我国实践中的作用,探讨了刑法对中间时法效力亟待完善的问题.